Fig. REF  shows \(\Delta \) GAP values for recommendation algorithms among the three user groups. As can be seen, Niches users receive significantly higher average \(\Delta \) GAP values followed by Diverse and Bestseller-focused users, respectively. This finding confirms the results of the Abdollahpouri et al. [1]} study and suggests that the popularity bias affects Niche users the most, that is, despite being interested in unpopular items, they receive recommendations of popular items. Interestingly, although the Bestseller-focused group receives the most favorable recommendations, the average \(\Delta \) GAP is \(126.55\) , revealing how algorithms can propagate the popularity bias even further than the Bestseller-focused user groups' interest in popular items. Fig.  REF  further illustrates that algorithms investigated in this study show similar behavior in terms of popularity bias among different user groups. Moreover, in line with our analysis in section REF , Random, MF, and NMF models provide the fairest recommendations, while MostPop, BPR, and NeuMF suffer from the propagation of popularity bias across all user groups.
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